Intelligent CIO Middle East Issue 15 | Page 60

INTELLIGENT BRANDS // Enterprise Security
Because of these shortcomings , 49 % have prioritized investment in personnel / training , 42 % are looking to make detection and security operations centre upgrades and 29 % plan to invest in integrating incident response into their analytics programs in the coming years .
“ One of the best ways to overcome shortages in staffing and funding is through automation ,” said SANS senior instructor and author of the report , Dave Shackleford . “ Machine learning offers insights that could help less-skilled analysts with faster detection , automatic reuse of patterns detected and more , leading to related improvements in risk posture .”
In this survey , 54 % of respondents rated their programs as being “ Fairly automated ,” while only 4 % considered their programs to be fully automated . Unfortunately , only 22 % said they deployed machine analytics to enable better , faster decision making , while 54 % said their programs did not use machine learning as part of their analytics programs , and 24 % didn ’ t know .
“ Analytics are an absolute necessity in today ’ s threat environment and it is encouraging to see that IT teams are making positive advances in this regard . But while results show an increasing usage , our survey highlights that there is still much room for improvement in the use of security analytics ,” concluded Baltagi .
Financial malware attacks increased in Q4 2016 In the fourth quarter of 2016 , the number of users that encountered malware capable of stealing money or valuable financial information reached 319,000 , 22.49 % more than in the same period in 2015 . An increase in the number of attacks was spotted during the White Friday and the holiday period , according to Kaspersky Lab research .
The holiday season is an attractive period of time , not only for retailers experiencing a high demand for their products and shoppers looking for great deals , but also for cyber criminals who don ’ t hesitate to explore new opportunities to exploit people illegally , at a time of year when more users are spending money online than usual .
At end of 2016 , Kaspersky Lab researchers conducted a retrospective look at the cyber threats landscape during the holiday period ( October , November and December ) in the last three years . The main conclusion of their analysis was that criminals are trying to tie their malicious campaigns to specific holiday dates .
Dynamics of attacks with financial malware during Q4 2016 ( holiday period ) Analysis of the holiday period in 2016 showed that last year ’ s season wasn ’ t the exception . Kaspersky Lab protection technologies detected attacks against 22.49 % more users than in the same period in 2015 . This means that after a decrease in 2014 , cybercriminals are again investing in developing malware capable of stealing financial data , such as credit card information and online banking credentials .
As the dynamics of attacks in November 2016 showed , the most attractive day of the fall-winter holidays for cybercriminals is Cyber Monday- a day dedicated to online sales and shopping worldwide . In November 2016 , Kaspersky Lab protection technologies detected a clear spike in the number of users attacked , and on November 28th ( Cyber Monday ) there were twice as many users attacked than during the previous day .
When it comes to the White Friday and the holiday periods , the pattern is different , with the spikes in attack dynamics occurring
one or two days prior to the actual holiday dates . These differences in malicious behaviour can be explained by the different nature of the holidays . Unlike White Friday and the holiday period , Cyber Monday is all about online sales worldwide , thus criminals see more sense in focusing their malicious campaigns on this particular date .
To reach their goals , criminals used one of 30 families of banking trojans , consistently tracked by Kaspersky Lab . Five of these are the most widespread : Zbot , Nymaim , Shiotob , Gozi and Neurevt . These trojans are responsible for attacks against 92.35 % of users in the holiday period .
“ Data on the dynamics of attacks shows that financial malware operators tried to attach their activity to particular dates in 2016 , and the holiday season ’ s contribution to the number of financial malicious attacks during this time is clearly visible . Financial malware attacks are on the rise again and all their targets – from owners and clients of e-shops , to credit card holders and banks – should be aware of the dangers and take adequate steps to stay safe . As a holiday season follow-up protection measure , we advise shoppers who used their credit cards to buy presents and goods during last three months to keep an eye on their financial transaction information in the coming months . Typically , criminals don ’ t start to withdraw money from stolen cards right after the theft . They often wait for several weeks or even months to prepare for cashing out first ,” said Oleg Kupreev , security expert at Kaspersky Lab .
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